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The University of Southampton
µ-VIS: Multidisciplinary, Multiscale, Microtomographic Volume Imaging

3D X-ray Histology (XRH)

Publications

This section lists the research outputs like peer-reviewed publications in scientific journals and conference proceedings related to 3D X-ray Histology generated by our group.

Peer-reviewed publications in scientific journals

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Rossides C, Pender SLF and Schneider P (2021), "3D cyclorama for digital unrolling and visualisation of deformed tubes", Scientific Reports., jul, 2021. Vol. 11(1) Springer Science and Business Media LLC.
Abstract: Colonic crypts are tubular glands that multiply through a symmetric branching process called crypt fission. During the early stages of colorectal cancer, the normal fission process is disturbed, leading to asymmetrical branching or budding. The challenging shapes of the budding crypts make it difficult to prepare paraffin sections for conventional histology, resulting in colonic cross sections with crypts that are only partially visible. To study crypt budding in situ and in three dimensions (3D), we employ X-ray micro-computed tomography to image intact colons, and a new method we developed (3D cyclorama) to digitally unroll them. Here, we present, verify and validate our ‘3D cyclorama’ method that digitally unrolls deformed tubes of non-uniform thickness. It employs principles from electrostatics to reform the tube into a series of onion-like surfaces, which are mapped onto planar panoramic views. This enables the study of features extending over several layers of the tube’s depth, demonstrated here by two case studies: (i) microvilli in the human placenta and (ii) 3D-printed adhesive films for drug delivery. Our 3D cyclorama method can provide novel insights into a wide spectrum of applications where digital unrolling or flattening is necessary, including long bones, teeth roots and ancient scrolls.
BibTeX:
@article{Rossides2021,
  author = {Charalambos Rossides and Sylvia L. F. Pender and Philipp Schneider},
  title = {3D cyclorama for digital unrolling and visualisation of deformed tubes},
  journal = {Scientific Reports},
  publisher = {Springer Science and Business Media LLC},
  year = {2021},
  volume = {11},
  number = {1},
  url = {https://www.nature.com/articles/s41598-021-93184-x},
  doi = {10.1038/s41598-021-93184-x}
}
Currie HAL, Martin NF, Garcia GE, Davis FM and Kemp PS (2020), "A mechanical approach to understanding the impact of the nematode Anguillicoloides crassus on the European eel swimbladder", Journal of Experimental Biology., jul, 2020. Vol. 223(17), pp. jeb219808. The Company of Biologists Ltd.
Abstract: One of the most detrimental factors in the drastic decline of the critically endangered European eel (Anguilla anguilla) was the inadvertent introduction of the invasive nematode Anguillicoloides crassus. Infection primarily affects the swimbladder, a gas-filled organ that enables the eel to control its depth in the water. A reduction in swimbladder function may be fatal for eel undergoing their spawning migration to the Sargasso Sea, a journey of over 5000 km. Although the physiological damage caused by this invasive parasite is well studied through the use of quantifiable gross pathological indices, providing a good measure of the swimbladder health status, they cannot separate the role of mechanical and morphological damage. Our study examined the appropriateness of three commonly used indices as a measure of mechanical damage by performing uniaxial tensile tests on swimbladder specimens obtained from an infected eel population. When the test results were compared with the gross pathological indices it was found that thickness correlated most strongly with mechanical damage, both confirming and, more importantly, explaining the counterintuitive findings of earlier work. In a damaged swimbladder, the immune response leads to a trade-off; increasing wall thickness raises the pressure required for organ rupture but decreases strength. The results indicate that for moderate infection the mechanical integrity of the swimbladder can be maintained. For severe infection, however, a reduction in mechanical integrity may reach a tipping point, thereby affecting the successful completion of their oceanic migration.
BibTeX:
@article{Currie2020,
  author = {Currie, Helen A. L. and Martin, Nicholas Flores and Garcia, Gerardo Espindola and Davis, Frances M. and Kemp, Paul S.},
  title = {A mechanical approach to understanding the impact of the nematode Anguillicoloides crassus on the European eel swimbladder},
  journal = {Journal of Experimental Biology},
  publisher = {The Company of Biologists Ltd},
  year = {2020},
  volume = {223},
  number = {17},
  pages = {jeb219808},
  url = {https://jeb.biologists.org/content/jexbio/223/17/jeb219808.full.pdf},
  doi = {10.1242/jeb.219808}
}
Lewis RM and Pearson-Farr JE (2020), "Multiscale three-dimensional imaging of the placenta", Placenta., feb, 2020. Elsevier BV.
Abstract: Placental function involves multiple different processes which operate at different scales from centimetres to nanometres. Everything that the placenta does from mediating blood flow to gene expression, occurs within a three-dimensional anatomical framework. This review outlines how multiscale three-dimensional imaging approaches can provide insight into placental structure and function. Three-dimensional imaging approaches include microCT, confocal, super resolution, light-sheet, and serial block-face scanning electron microscopy. Used together, these approaches allow three-dimensional imaging of the placenta across the scales at which different processes occur. Three-dimensional imaging illustrates the spatial relationships between structures and visualises structures that are not clearly apparent in two-dimensions. Understanding the three-dimensional structure of the placenta enables exploration of the relationship between structure and function, including through the development of computational models based on realistic geometries. Three-dimensional imaging approaches will enhance our understanding of placental function in health and disease.
BibTeX:
@article{Lewis_2020,
  author = {Rohan M. Lewis and Jennifer E. Pearson-Farr},
  title = {Multiscale three-dimensional imaging of the placenta},
  journal = {Placenta},
  publisher = {Elsevier BV},
  year = {2020},
  url = {https://www.sciencedirect.com/science/article/pii/S0143400420300345},
  doi = {10.1016/j.placenta.2020.01.016}
}
Zdora M-C, Thibault P, Kuo W, Fernandez V, Deyhle H, Vila-Comamala J, Olbinado MP, Rack A, Lackie PM, Katsamenis OL, Lawson MJ, Kurtcuoglu V, Rau C, Pfeiffer F and Zanette I (2020), "X-ray phase tomography with near-field speckles for three-dimensional virtual histology", Optica., sep, 2020. Vol. 7(9), pp. 1221. The Optical Society.
Abstract: High-contrast, high-resolution imaging of biomedical specimens is indispensable for studying organ function and pathologies. Conventional histology, the gold standard for soft-tissue visualization, is limited by its anisotropic spatial resolution, elaborate sample preparation, and lack of quantitative image information. X-ray absorption or phase tomography have been identified as promising alternatives enabling non-destructive, distortion-free three-dimensional (3D) imaging. However, reaching sufficient contrast and resolution with a simple experimental procedure remains a major challenge. Here, we present a solution based on x-ray phase tomography through speckle-based imaging (SBI). We demonstrate on a mouse kidney that SBI delivers comprehensive 3D maps of hydrated, unstained soft tissue, revealing its microstructure and delivering quantitative tissue-density values at a density resolution of better than 2mg/cm3 and spatial resolution of better than 8 µm. We expect that SBI virtual histology will find widespread application in biomedicine and will open up new possibilities for research and histopathology.
BibTeX:
@article{Zdora2020,
  author = {Marie-Christine Zdora and Pierre Thibault and Willy Kuo and Vincent Fernandez and Hans Deyhle and Joan Vila-Comamala and Margie P. Olbinado and Alexander Rack and Peter M. Lackie and Orestis L. Katsamenis and Matthew J. Lawson and Vartan Kurtcuoglu and Christoph Rau and Franz Pfeiffer and Irene Zanette},
  title = {X-ray phase tomography with near-field speckles for three-dimensional virtual histology},
  journal = {Optica},
  publisher = {The Optical Society},
  year = {2020},
  volume = {7},
  number = {9},
  pages = {1221},
  url = {https://www.osapublishing.org/optica/abstract.cfm?uri=optica-7-9-1221},
  doi = {10.1364/optica.399421}
}
Karavasili C, Andreadis DA, Katsamenis OL, Panteris E, Anastasiadou P, Kakazanis Z, Zoumpourlis V, Markopoulou CK, Koutsopoulos S, Vizirianakis IS and Fatouros DG (2019), "Synergistic antitumor potency of a self-assembling peptide hydrogel for the local co-delivery of doxorubicin and curcumin in the treatment of head and neck cancer.", Molecular pharmaceutics., June, 2019. Vol. 16(6), pp. 2326-2341. American Chemical Society (ACS).
Abstract: Combination therapy has been conferred with manifold assets leveraging the synergy of different agents to achieve a sufficient therapeutic outcome with lower administered drug doses and reduced side effects. The therapeutic potency of a self-assembling peptide hydrogel for the co-delivery of doxorubicin and curcumin was assessed against head and neck cancer cells. The dual loaded peptide hydrogel enabled control over the rate of drug release based on drug's aqueous solubility. A significantly enhanced cell growth inhibitory effect was observed after treatment with the combination drug-loaded hydrogel formulations compared to the respective combination drug solution. The synergistic pharmacological effect of selected hydrogel formulations was further confirmed with enhanced apoptotic cell response, interference in cell cycle progression, and significantly altered apoptotic/anti-apoptotic gene expression profiles obtained in dose levels well below the half-maximal inhibitory concentrations of both drugs. The in vivo antitumor efficacy of the drug-loaded peptide hydrogel formulation was confirmed in HSC-3 cell-xenografted severe combined immunodeficient mice and visualized with μCT imaging. Histological and terminal deoxynucleotidyl transferase dUTP nick end labeling assay analyses of major organs were implemented to assess the safety of the topically administered hydrogel formulation. Overall, results demonstrated the therapeutic utility of the dual drug-loaded peptide hydrogel as a pertinent approach for the local treatment of head and neck cancer.
BibTeX:
@article{Karavasili2019,
  author = {Karavasili, Christina and Andreadis, Dimitrios A. and Katsamenis, Orestis L. and Panteris, Emmanuel and Anastasiadou, Pinelopi and Kakazanis, Zacharias and Zoumpourlis, Vasilis and Markopoulou, Catherine K. and Koutsopoulos, Sotirios and Vizirianakis, Ioannis S. and Fatouros, Dimitrios G.},
  title = {Synergistic antitumor potency of a self-assembling peptide hydrogel for the local co-delivery of doxorubicin and curcumin in the treatment of head and neck cancer.},
  journal = {Molecular pharmaceutics},
  publisher = {American Chemical Society (ACS)},
  year = {2019},
  volume = {16},
  number = {6},
  pages = {2326--2341},
  url = {https://pubs.acs.org/doi/10.1021/acs.molpharmaceut.8b01221},
  doi = {10.1021/acs.molpharmaceut.8b01221}
}
Karavasili C, Andreadis DA, Katsamenis OL, Panteris E, Anastasiadou P, Kakazanis Z, Zoumpourlis V, Markopoulou CK, Koutsopoulos S, Vizirianakis IS and others (2019), "Synergistic anti-tumour potency of a self-assembling peptide hydrogel for the local co-delivery of doxorubicin and curcumin in the treatment of head and neck cancer", Molecular pharmaceutics. ACS Publications.
Abstract: Combination therapy has been conferred with manifold assets leveraging the synergy of different agents to achieve a sufficient therapeutic outcome with lower administered drug doses and reduced side effects. The therapeutic potency of a self-assembling peptide hydrogel for the co-delivery of doxorubicin and curcumin was assessed against head and neck cancer cells. The dual loaded peptide hydrogel enabled control over the rate of drug release based on drug’s aqueous solubility. A significantly enhanced cell growth inhibitory effect was observed after treatment with the combination drug-loaded hydrogel formulations compared to the respective combination drug solution. The synergistic pharmacological effect of selected hydrogel formulations was further confirmed with enhanced apoptotic cell response, interference in cell cycle progression, and significantly altered apoptotic/anti-apoptotic gene expression profiles obtained in dose levels well below the half-maximal inhibitory concentrations of both drugs. The in vivo antitumor efficacy of the drug-loaded peptide hydrogel formulation was confirmed in HSC-3 cell-xenografted severe combined immunodeficient mice and visualized with μCT imaging. Histological and terminal deoxynucleotidyl transferase dUTP nick end labeling assay analyses of major organs were implemented to assess the safety of the topically administered hydrogel formulation. Overall, results demonstrated the therapeutic utility of the dual drug-loaded peptide hydrogel as a pertinent approach for the local treatment of head and neck cancer.
BibTeX:
@article{karavasili2019synergistic,
  author = {Karavasili, Christina and Andreadis, Dimitrios A and Katsamenis, Orestis L and Panteris, Emmanuel and Anastasiadou, Pinelopi and Kakazanis, Zacharias and Zoumpourlis, Vasilis and Markopoulou, Catherine K and Koutsopoulos, Sotirios and Vizirianakis, Ioannis S and others},
  title = {Synergistic anti-tumour potency of a self-assembling peptide hydrogel for the local co-delivery of doxorubicin and curcumin in the treatment of head and neck cancer},
  journal = {Molecular pharmaceutics},
  publisher = {ACS Publications},
  year = {2019},
  url = {https://pubs.acs.org/doi/abs/10.1021/acs.molpharmaceut.8b01221},
  doi = {10.1021/acs.molpharmaceut.8b01221}
}
Katsamenis OL, Olding M, Warner JA, Chatelet DS, Jones MG, Sgalla G, Smit B, Larkin OJ, Haig I, Richeldi L and others (2019), "X-ray micro-computed tomography for non-destructive 3D X-ray histology", The American journal of pathology., May, 2019. Elsevier.
Abstract: Historically, micro-computed tomography has been considered unsuitable for histological analysis of unstained formalin-fixed and paraffin-embedded (FFPE) soft tissue biopsies due to a lack of image contrast between the tissue and the paraffin. However, we recently demonstrated that μCT can successfully resolve microstructural detail in routinely prepared tissue specimens. Here, we illustrate how μCT imaging of standard FFPE biopsies can be seamlessly integrated into conventional histology workflows, enabling non-destructive three-dimensional (3D) X-ray histology, the use and benefits of which we showcase for the exemplar of human lung biopsy specimens. This technology advancement was achieved through manufacturing a first-of-kind μCT scanner for X-ray histology and developing optimised imaging protocols, which do not require any additional sample preparation. 3D X-ray histology allows for non-destructive 3D imaging of tissue microstructure, resolving structural connectivity and heterogeneity of complex tissue networks, such as the vascular or the respiratory tract. We also demonstrate that 3D X-ray histology can yield consistent and reproducible image quality, enabling quantitative assessment of tissue’s 3D microstructures, which is inaccessible to conventional two-dimensional histology. Being non-destructive the technique does not interfere with histology workflows, permitting subsequent tissue characterisation by means of conventional light microscopy-based histology, immunohistochemistry, and immunofluorescence. 3D X-ray histology can be readily applied to a plethora of archival materials, yielding unprecedented opportunities in diagnosis and research of disease.
BibTeX:
@article{Katsamenis2019,
  author = {Katsamenis, Orestis L and Olding, Michael and Warner, Jane A and Chatelet, David S and Jones, Mark G and Sgalla, Giacomo and Smit, Bennie and Larkin, Oliver J and Haig, Ian and Richeldi, Luca and others},
  title = {X-ray micro-computed tomography for non-destructive 3D X-ray histology},
  journal = {The American journal of pathology},
  publisher = {Elsevier},
  year = {2019},
  note = {In Press, Accepted Manuscript},
  url = {https://www.sciencedirect.com/science/article/pii/S0002944019302068},
  doi = {10.1016/j.ajpath.2019.05.004}
}
Robinson SK, Ramsden JJ, Warner J, Lackie PM and Roose T (2019), "Correlative 3D Imaging and Microfluidic Modelling of Human Pulmonary Lymphatics using Immunohistochemistry and High-resolution μCT", Scientific reports. Vol. 9(1), pp. 6415. Nature Publishing Group.
Abstract: Lung lymphatics maintain fluid homoeostasis by providing a drainage system that returns fluid, cells and metabolites to the circulatory system. The 3D structure of the human pulmonary lymphatic network is essential to lung function, but it is poorly characterised. Image-based 3D mathematical modelling of pulmonary lymphatic microfluidics has been limited by the lack of accurate and representative image geometries. This is due to the microstructural similarity of the lymphatics to the blood vessel network, the lack of lymphatic-specific biomarkers, the technical limitations associated with image resolution in 3D, and sectioning artefacts present in 2D techniques. We present a method that combines lymphatic specific (D240 antibody) immunohistochemistry (IHC), optimised high-resolution X-ray microfocus computed tomography (μCT) and finite-element mathematical modelling to assess the function of human peripheral lung tissue. The initial results identify lymphatic heterogeneity within and between lung tissue. Lymphatic vessel volume fraction and fractal dimension significantly decreases away from the lung pleural surface (p < 0.001, n = 25 and p < 0.01, n = 20, respectively). Microfluidic modelling successfully shows that in lung tissue the fluid derived from the blood vessels drains through the interstitium into the lymphatic vessel network and this drainage is different in the subpleural space compared to the intralobular space. When comparing lung tissue from health and disease, human pulmonary lymphatics were significantly different across five morphometric measures used in this study (p ≤ 0.0001). This proof of principle study establishes a new engineering technology and workflow for further studies of pulmonary lymphatics and demonstrates for the first time the combination of correlative μCT and IHC to enable 3D mathematical modelling of human lung microfluidics at micrometre resolution.
BibTeX:
@article{Robinson2019,
  author = {Robinson, Stephanie K. and Ramsden, Jonathan J. and Warner, Jane and Lackie, Peter M. and Roose, Tiina},
  title = {Correlative 3D Imaging and Microfluidic Modelling of Human Pulmonary Lymphatics using Immunohistochemistry and High-resolution μCT},
  journal = {Scientific reports},
  publisher = {Nature Publishing Group},
  year = {2019},
  volume = {9},
  number = {1},
  pages = {6415},
  url = {https://www.nature.com/articles/s41598-019-42794-7#Ack1},
  doi = {10.1038/s41598-019-42794-7}
}
Koo H-K, Vasilescu DM, Booth S, Hsieh A, Katsamenis OL, Fishbane N, Elliott WM, Kirby M, Lackie P, Sinclair I, Warner JA, Cooper JD, Coxson HO, Paré PD, Hogg JC and Hackett T-L (2018), "Small airways disease in mild and moderate chronic obstructive pulmonary disease: a cross-sectional study.", The Lancet. Respiratory medicine., August, 2018. Vol. 6, pp. 591-602.
Abstract: The concept that small conducting airways less than 2 mm in diameter become the major site of airflow obstruction in chronic obstructive pulmonary disease (COPD) is well established in the scientific literature, and the last generation of small conducting airways, terminal bronchioles, are known to be destroyed in patients with very severe COPD. We aimed to determine whether destruction of the terminal and transitional bronchioles (the first generation of respiratory airways) occurs before, or in parallel with, emphysematous tissue destruction. In this cross-sectional analysis, we applied a novel multiresolution CT imaging protocol to tissue samples obtained using a systematic uniform sampling method to obtain representative unbiased samples of the whole lung or lobe of smokers with normal lung function (controls) and patients with mild COPD (Global Initiative for Chronic Obstructive Lung Disease [GOLD] stage 1), moderate COPD (GOLD 2), or very severe COPD (GOLD 4). Patients with GOLD 1 or GOLD 2 COPD and smokers with normal lung function had undergone lobectomy and pneumonectomy, and patients with GOLD 4 COPD had undergone lung transplantation. Lung tissue samples were used for stereological assessment of the number and morphology of terminal and transitional bronchioles, airspace size (mean linear intercept), and alveolar surface area. Of the 34 patients included in this study, ten were controls (smokers with normal lung function), ten patients had GOLD 1 COPD, eight had GOLD 2 COPD, and six had GOLD 4 COPD with centrilobular emphysema. The 34 lung specimens provided 262 lung samples. Compared with control smokers, the number of terminal bronchioles decreased by 40% in patients with GOLD 1 COPD (p=0·014) and 43% in patients with GOLD 2 COPD (p=0·036), the number of transitional bronchioles decreased by 56% in patients with GOLD 1 COPD (p=0·0001) and 59% in patients with GOLD 2 COPD (p=0·0001), and alveolar surface area decreased by 33% in patients with GOLD 1 COPD (p=0·019) and 45% in patients with GOLD 2 COPD (p=0·0021). These pathological changes were found to correlate with lung function decline. We also showed significant loss of terminal and transitional bronchioles in lung samples from patients with GOLD 1 or GOLD 2 COPD that had a normal alveolar surface area. Remaining small airways were found to have thickened walls and narrowed lumens, which become more obstructed with increasing COPD GOLD stage. These data show that small airways disease is a pathological feature in mild and moderate COPD. Importantly, this study emphasises that early intervention for disease modification might be required by patients with mild or moderate COPD. Canadian Institutes of Health Research.
BibTeX:
@article{Koo2018,
  author = {Koo, Hyun-Kyoung and Vasilescu, Dragoş M and Booth, Steven and Hsieh, Aileen and Katsamenis, Orestis L and Fishbane, Nick and Elliott, W Mark and Kirby, Miranda and Lackie, Peter and Sinclair, Ian and Warner, Jane A and Cooper, Joel D and Coxson, Harvey O and Paré, Peter D and Hogg, James C and Hackett, Tillie-Louise},
  title = {Small airways disease in mild and moderate chronic obstructive pulmonary disease: a cross-sectional study.},
  journal = {The Lancet. Respiratory medicine},
  year = {2018},
  volume = {6},
  pages = {591--602},
  doi = {10.1016/S2213-2600(18)30196-6}
}
Wollatz L, Johnston SJ, Lackie PM and Cox SJ (2017), "3D Histopathology—a Lung Tissue Segmentation Workflow for Microfocus X-ray-Computed Tomography Scans", Journal of Digital Imaging. , pp. 1-10. Springer.
Abstract: Lung histopathology is currently based on the analysis of 2D sections of tissue samples. The use of microfocus X-ray-computed tomography imaging of unstained soft tissue can provide high-resolution 3D image datasets in the range of 2–10 μm without affecting the current diagnostic workflow. Important details of structural features such as the tubular networks of airways and blood vessels are contained in these datasets but are difficult and time-consuming to identify by manual image segmentation. Providing 3D structures permits a better understanding of tissue functions and structural interrelationships. It also provides a more complete picture of heterogeneous samples. In addition, 3D analysis of tissue structure provides the potential for an entirely new level of quantitative measurements of this structure that have previously been based only on extrapolation from 2D sections. In this paper, a workflow for segmenting such 3D images semi-automatically has been created using and extending the ImageJ open-source software and key steps of the workflow have been integrated into a new ImageJ plug-in called LungJ. Results indicate an improved workflow with a modular organization of steps facilitating the optimization for different sample and scan properties with expert input as required. This allows for incremental and independent optimization of algorithms leading to faster segmentation. Representation of the tubular networks in samples of human lung, building on those segmentations, has been demonstrated using this approach.
BibTeX:
@article{Wollatz2017,
  author = {Wollatz, Lasse and Johnston, Steven J and Lackie, Peter M and Cox, Simon J},
  title = {3D Histopathology—a Lung Tissue Segmentation Workflow for Microfocus X-ray-Computed Tomography Scans},
  journal = {Journal of Digital Imaging},
  publisher = {Springer},
  year = {2017},
  pages = {1--10},
  url = {https://link.springer.com/article/10.1007/s10278-017-9966-5},
  doi = {10.1007/s10278-017-9966-5}
}
Jones MG, Fabre A, Schneider P, Cinetto F, Sgalla G, Mavrogordato M, Jogai S, Alzetani A, Marshall BG, O’Reilly KM and others (2016), "Three-dimensional characterization of fibroblast foci in idiopathic pulmonary fibrosis", JCI insight. Vol. 1(5) NIH Public Access.
Abstract: In idiopathic pulmonary fibrosis (IPF), the fibroblast focus is a key histological feature representing active fibroproliferation. On standard 2D pathologic examination, fibroblast foci are considered small, distinct lesions, although they have been proposed to form a highly interconnected reticulum as the leading edge of a “wave” of fibrosis. Here, we characterized fibroblast focus morphology and interrelationships in 3D using an integrated micro-CT and histological methodology. In 3D, fibroblast foci were morphologically complex structures, with large variations in shape and volume (range, 1.3 × 104 to 9.9 × 107 μm3). Within each tissue sample numerous multiform foci were present, ranging from a minimum of 0.9 per mm3 of lung tissue to a maximum of 11.1 per mm3 of lung tissue. Each focus was an independent structure, and no interconnections were observed. Together, our data indicate that in 3D fibroblast foci form a constellation of heterogeneous structures with large variations in shape and volume, suggesting previously unrecognized plasticity. No evidence of interconnectivity was identified, consistent with the concept that foci represent discrete sites of lung injury and repair.
BibTeX:
@article{Jones2016,
  author = {Jones, Mark G and Fabre, Aurélie and Schneider, Philipp and Cinetto, Francesco and Sgalla, Giacomo and Mavrogordato, Mark and Jogai, Sanjay and Alzetani, Aiman and Marshall, Ben G and O’Reilly, Katherine MA and others},
  title = {Three-dimensional characterization of fibroblast foci in idiopathic pulmonary fibrosis},
  journal = {JCI insight},
  publisher = {NIH Public Access},
  year = {2016},
  volume = {1},
  number = {5},
  url = {https://insight.jci.org/articles/view/86375},
  doi = {10.1172/jci.insight.86375}
}
Scott A, Vasilescu D, Seal K, Keyes S, Mavrogordato M, Hogg J, Sinclair I, Warner J, Hackett T and Lackie P (2015), "Three dimensional imaging of paraffin embedded human lung tissue samples by micro-computed tomography", PLoS ONE., June, 2015. , pp. 1-10.
Abstract: Background: understanding the three-dimensional (3-D) micro-architecture of lung tissue can provide insights into the pathology of lung disease. Micro computed tomography (mu CT) has previously been used to elucidate lung 3D histology and morphometry in fixed samples that have been stained with contrast agents or air inflated and dried. However, non-destructive microstructural 3D imaging of formalin-fixed paraffin embedded (FFPE) tissues would facilitate retrospective analysis of extensive tissue archives of lung FFPE lung samples with linked clinical data.

Methods: FFPE human lung tissue samples (n = 4) were scanned using a Nikon metrology mu CT scanner. Semi-automatic techniques were used to segment the 3D structure of airways and blood vessels. Airspace size (mean linear intercept, Lm) was measured on mu CT images and on matched histological sections from the same FFPE samples imaged by light microscopy to validate mu CT imaging.

Results: the mu CT imaging protocol provided contrast between tissue and paraffin in FFPE samples (15mm x 7mm). Resolution (voxel size 6.7 mu m) in the reconstructed images was sufficient for semi-automatic image segmentation of airways and blood vessels as well as quantitative airspace analysis. The scans were also used to scout for regions of interest, enabling time-efficient preparation of conventional histological sections. The Lm measurements from mu CT images were not significantly different to those from matched histological sections.

Conclusion: we demonstrated how non-destructive imaging of routinely prepared FFPE samples by laboratory mu CT can be used to visualize and assess the 3D morphology of the lung including by morphometric analysis.
BibTeX:
@article{ScottVasilescuSealEtAl2015,
  author = {A.E. Scott and D.M. Vasilescu and K.A.D. Seal and S.D. Keyes and M.N. Mavrogordato and J.C. Hogg and I. Sinclair and J.A. Warner and T.L. Hackett and P.M. Lackie},
  title = {Three dimensional imaging of paraffin embedded human lung tissue samples by micro-computed tomography},
  journal = {PLoS ONE},
  year = {2015},
  pages = {1--10},
  url = {http://eprints.soton.ac.uk/381745/}
}
Created by JabRef on 30/07/2021.

Conference proceedings

JabRef references
Matching entries: 0
settings...
Keeling G, Baark F, Katsamenis O, Reader A, Smith G, Terry S, Blower P and de Rosales RTM (2021), "[68Ga]Ga-THP-Pam: A PET radiotracer for imaging vascular calcification", Nuclear Medicine Communications., In Abstracts: British Nuclear Medicine Society Online Spring Meeting 18 -19 May 2021., October, 2021. Vol. 42(5), pp. 575-581. Ovid Technologies (Wolters Kluwer Health).
BibTeX:
@inproceedings{Keeling2021,
  author = {Keeling, George and Baark, Friedrich and Katsamenis, Orestis and Reader, Andrew and Smith, Gareth and Terry, Samantha and Blower, Philip and de Rosales, Rafael Torres Martin},
  title = {[68Ga]Ga-THP-Pam: A PET radiotracer for imaging vascular calcification},
  booktitle = {Abstracts: British Nuclear Medicine Society Online Spring Meeting 18 -19 May 2021},
  journal = {Nuclear Medicine Communications},
  publisher = {Ovid Technologies (Wolters Kluwer Health)},
  year = {2021},
  volume = {42},
  number = {5},
  pages = {575--581},
  url = {https://journals.lww.com/nuclearmedicinecomm/fulltext/2021/05000/abstracts__british_nuclear_medicine_society_online.15.aspx},
  doi = {10.1097/mnm.0000000000001180}
}
Keeling G, Baark F, Katsamenis O, Reader A, Smith G, Terry S, Blower P and de Rosales RlTM (2021), "[68Ga]Ga-THP-Pam: A PET radiotracer for imaging vascular calcification", In 34th Annual Congress of the European Association of Nuclear Medicine, 06 -09 Oct 2021., October, 2021.
BibTeX:
@inproceedings{Keeling2021a,
  author = {Keeling, George and Baark, Friedrich and Katsamenis, Orestis and Reader, Andrew and Smith, Gareth and Terry, Samantha and Blower, Philip and de Rosales, Rafae l Torres Martin},
  title = {[68Ga]Ga-THP-Pam: A PET radiotracer for imaging vascular calcification},
  booktitle = {34th Annual Congress of the European Association of Nuclear Medicine, 06 -09 Oct 2021},
  year = {2021},
  note = {Oct 06 -09},
  url = {https://www.wmis.org/wmic-2021-2/}
}
Keeling G, Baark F, Katsamenis O, Reader A, Smith G, Terry S, Blower P and de Rosales RlTM (2021), "[68Ga]Ga-THP-Pam: A PET radiotracer for imaging vascular calcification", In World Molecular Imaging Society (WMIC2021), 20 -23 Oct 2021., October, 2021.
BibTeX:
@inproceedings{Keeling2021b,
  author = {Keeling, George and Baark, Friedrich and Katsamenis, Orestis and Reader, Andrew and Smith, Gareth and Terry, Samantha and Blower, Philip and de Rosales, Rafae l Torres Martin},
  title = {[68Ga]Ga-THP-Pam: A PET radiotracer for imaging vascular calcification},
  booktitle = {World Molecular Imaging Society (WMIC2021), 20 -23 Oct 2021},
  year = {2021},
  note = {Oct 20 -23},
  url = {https://eanm21.eanm.org}
}
Basford PJ, Konstantinopoulou E, Katsamenis OL, Boardman R, Schneider P, Lackie P and Cox S (2020), "A sample and data management system for ?CT-based X-ray histology", In Tomography for Scientific Advancement - 10th Edition (03/09/20)., September, 2020.
Abstract: While setting up a facility for X-ray histology (XRH) [1] in Southampton the challenge arose of how to manage samples, data and associated metadata. This is challenging as the same sample can be analysed multiple times in different states and different modalities including micro-computed tomography (\muCT), conventional (2D) thin section-based histology/whole-slide imaging or immunohistochemistry. A fresh piece of tissue may be imaged, frozen, imaged, embedded in paraffin wax, imaged, and sectioned and processed using histological techniques, all of which needs to be included attached in the sample record. Moreover, sample and data management system needed to be user-friendly. These requirements have led to the development of XRHMS, a management system to keep track of all samples within the facility, their data and their metadata, as summarised in Figure 1. Metadata of interest about the sample includes details about the tissue type and origin, preparation, storage requirements and current location.

Figure 1 Information included in XRHMS
The combination of storing raw / processed image data and metadata requires careful architectural decisions, and is built on previous work in this area [2] and uses a database for the metadata and file system for the ?CT data. The system can store data from multiple different acquisition systems and digitised histological slides, and is designed to be easily extensible. The XRHMS provides full tracking and accounting of all samples/data/processes and enables cross-linking between related datasets.
The XRHMS also forms the basis for automation of data processing, with preview images and slices generated automatically, as well as performing basic pre-processing, with additional features planned. The system can generate summary reports about the samples containing information about the scans performed and related images. These provide a useful overview of the scan and data interpretation guidance for people not familiar with the technique or viewing 3D datasets.
BibTeX:
@inproceedings{Basford2020,
  author = {Philip J Basford and Elena Konstantinopoulou and Orestis L. Katsamenis and Richard Boardman and Philipp Schneider and Peter Lackie and Simon Cox},
  title = {A sample and data management system for ?CT-based X-ray histology},
  booktitle = {Tomography for Scientific Advancement - 10th Edition (03/09/20)},
  year = {2020},
  url = {https://eprints.soton.ac.uk/448103/}
}
Basford PJ, Katsamenis OL, Konstantinopoulou E, Boardman R, Schneider P, Lackie P and Cox S (2020), "Data management and automatic reporting for 3D X-ray histology", In 7th Digital Pathology & AI Congress: Europe (03/12/20 - 04/12/20)., December, 2020.
BibTeX:
@inproceedings{Basford2020a,
  author = {Philip J Basford and Orestis L. Katsamenis and Elena Konstantinopoulou and Richard Boardman and Philipp Schneider and Peter Lackie and Simon Cox},
  title = {Data management and automatic reporting for 3D X-ray histology},
  booktitle = {7th Digital Pathology & AI Congress: Europe (03/12/20 - 04/12/20)},
  year = {2020},
  url = {https://eprints.soton.ac.uk/448069/}
}
Ho EML, Katsamenis OL, Thomas G, Lackie P and Schneider P (2020), "3D X-ray histology for detection of metastasis in whole lymph node specimens", In 7th Digital Pathology & AI Congress: Europe (03/12/20 - 04/12/20)., December, 2020.
BibTeX:
@inproceedings{Ho2020,
  author = {Elaine Ming Li Ho and Orestis L. Katsamenis and Gareth Thomas and Peter Lackie and Philipp Schneider},
  title = {3D X-ray histology for detection of metastasis in whole lymph node specimens},
  booktitle = {7th Digital Pathology & AI Congress: Europe (03/12/20 - 04/12/20)},
  year = {2020},
  url = {https://eprints.soton.ac.uk/448077/}
}
Ho EML, Lackie P, Katsamenis OL and Schneider P (2020), "Adding a new dimension to soft tissue imaging through correlative 2D thin-section &amp; 3D X-ray histology", In STEM for BRITAIN (09/03/20)., March, 2020.
Abstract: Histology is the study of the microscopic structure of tissues such as lung, skin or brain. Classical histology techniques developed in the 18th century examine thin tissue sections under the microscope. These methods have underpinned many discoveries in modern biology and are still widely used today in biomedical research and the medical diagnosis of disease. However, classical histology only provides a 2 dimensional view of the 3 dimensional (3D) tissue features.
X-ray micro-computed tomography (\muCT) is non-destructive and generates 3D images of biological structures in the millimetre down to micron (1/1000 mm) scale, approaching that of standard light microscopy. Examples of biological structures in this range include capillaries, lung alveoli and even whole organs of small animals. As \muCT imaging is non-invasive and does not destroy the sample, the same specimens can subsequently be imaged in other ways, combining the benefits of several techniques to provide a comprehensive understanding of tissue microstructure in 3D. For example, having a 3D \muCT image of a specimen before it is cut into thin sections allows specific regions of the
specimen to be targeted for further analysis. This ensures that relevant portions of the specimen are studied in greater detail and reduces the chances of missing the feature of interest in the specimen. This project aims to develop a method for correlative \muCT and classical histology which is compatible with routine clinical practice for processing soft tissue biopsies. This method should be applicable to a range of soft tissues and provide good quality images of the entire specimen within a short timeframe of a few days. To this end, each stage of the workflow was analysed to identify potential issues and devise robust solutions.
Firstly, \muCT scanning of routinely processed soft tissue specimens is performed to obtain a 3D image of the specimen. The optimum \muCT imaging protocol is determined objectively using a semi-automated software tool for measuring image quality. Next, thin histology sections are cut and stained according to standard protocols. The sections are digitised and aligned to the 3D \muCT image, which corrects for any distortions occurring during classical histology processing. The 2D histology sections are then viewed in the
context of the 3D \muCT image with a custom-built intuitive interface.
This correlative imaging method extends classical histological techniques developed over hundreds of years with modern 3D imaging technology. It is anticipated that the method will facilitate imaging studies on a previously infeasible scale by collecting information about whole specimens in 3D, adding an entirely new dimension to our understanding of biological structure.
BibTeX:
@inproceedings{Ho2020a,
  author = {Elaine Ming Li Ho and Peter Lackie and Orestis L. Katsamenis and Philipp Schneider},
  title = {Adding a new dimension to soft tissue imaging through correlative 2D thin-section &amp; 3D X-ray histology},
  booktitle = {STEM for BRITAIN (09/03/20)},
  year = {2020},
  url = {https://eprints.soton.ac.uk/448070/}
}
Hough K, Anderson L, Katsamenis OL, Tourrel G, Chatelet D, Verschuur C and Newman T (2020), "Corroborating μCT and histological data to provide novel insight into the biological response to cochlear implantation at the electrode-tissue interface", In Tomography for Scientific Advancement - 10th Edition (03/09/20)., September, 2020.
Abstract: Cochlear implants are the most successful neuro-prostheses. They restore hearing by replacing the function of damaged sensory cells inside the cochlea (hearing part of the inner ear). Direct stimulation of the auditory nerve is driven through current generated at electrodes inserted into the cochlea. Despite the success of cochlear implants some individuals underperform or fail i.e. do not achieve the anticipated benefits. A significant proportion of the failures are not due to hardware or surgical factors but may also be due to the biological response at the electrode-tissue interface. As availability of human tissue to investigate the tissue response to cochlear implantation is limited, there is great need for effective in vivo models. We have established a mouse model to investigate the response at the electrode-tissue interface with the aim of understanding how the response to the implant may alter hearing performance, and how this is altered by different materials coating the array. Optimally designed, functional, electrode arrays have been surgically implanted into mice through the round window of the cochlea.

?CT imaging and visualisation has been used to obtain 3D structural information about the cochlea pre-implantation and to visualise the position of array to validate surgical technique post-implantation. Further work will involve implanting and recovering the mice then ?CT imaging immediately after culling to visualise any soft tissue damage caused by electrode insertion. The overall aim is to corroborate high resolution ?CT images of the mouse cochlea post-implantation with in-depth histological analysis of the tissue to provide essential insight into the biological response at the CI-tissue interface.
BibTeX:
@inproceedings{Hough2020,
  author = {Kate Hough and Lucy Anderson and Orestis L. Katsamenis and Guillaume Tourrel and David Chatelet and Carl Verschuur and Tracey Newman},
  title = {Corroborating μCT and histological data to provide novel insight into the biological response to cochlear implantation at the electrode-tissue interface},
  booktitle = {Tomography for Scientific Advancement - 10th Edition (03/09/20)},
  year = {2020},
  url = {https://eprints.soton.ac.uk/443745/}
}
Konstantinopoulou E, Basford PJ, Katsamenis OL, Boardman R, Chatelet D, Cox S, Schneider P and Lackie P (2020), "Automated PDF reporting system for X-ray histology (XRH) scan data", In 10th Annual Tomography for Scientific Advancement (ToScA) symposium (03/09/20)., September, 2020.
Abstract: Our X-ray histology (XRH) facility provides a micro-computed tomography (?CT) imaging service of unstained human and animal tissue samples from a wide array of diseases. These data are shared with biomedical researchers and clinicians who are often unfamiliar with this technology and its outputs. This creates the need to rapidly process and report XRH data in a comprehensive and easily accessible way, assuming no prior user knowledge of ?CT.
We created a semi-automated reporting system directly linked with our custom-built XRH sample management system (XRHMS) (Fig.1). To ensure cross-platform and multi-software compatibility, the system generates a report as augmented Portable Document Format (PDF).
The first page (Fig.2) contains sample information, photographs, and QR/DM codes linking it to the corresponding XRHMS entry. Subsequent pages list imaging settings and still images with a descriptive figure legend, linked to corresponding online videos. These videos (accessible through any web-browser and available for download) scroll through the stack and help visualise the scanned sample in different ways such as orthogonal views, maximum/average intensity projections and 3D renderings. Online videos make the report easily shareable by email (reasonable file-sizes). This allows users with the link to view videos in YouTube Viewer at the highest resolution available without needing specialist software. Links to useful resources, instructions on how to acknowledge the facility and XRH contact details come next. An appendix contains any additional views not shown in the main body of the report or other data (e.g. conventional 2D histology images).
Accompanying \muCT data with a PDF report brings together information about the sample, scan images and links to videos of 3D viewing modes. Such a reporting system is very valuable and not limited to the biomedical field as it can be applied to a range of different disciplines.
BibTeX:
@inproceedings{Konstantinopoulou2020,
  author = {Elena Konstantinopoulou and Philip J. Basford and Orestis L. Katsamenis and Richard Boardman and David Chatelet and Simon Cox and Philipp Schneider and Peter Lackie},
  title = {Automated PDF reporting system for X-ray histology (XRH) scan data},
  booktitle = {10th Annual Tomography for Scientific Advancement (ToScA) symposium (03/09/20)},
  year = {2020},
  url = {https://eprints.soton.ac.uk/448229/}
}
Konstantinopoulou E, Katsamenis OL, Broadbent B, Chatelet D, Basford PJ, Haig I, Roche W, Alzetani A, Schneider P and Lackie P (2020), "Potential assessment of lung samples by X-ray histology (XRH) during surgery", In 10th Annual Tomography for Scientific Advancement (ToScA) symposium (03/09/20)., September, 2020.
Abstract: More than 25,000 operations to remove all or part of a patient?s lung take place in Europe each year. The full extent and type of changes in lung structure due to disease may not be evident until surgery is underway. Immediate microanatomical assessment of removed tissue can guide and inform the surgical team.
We explored the feasibility of using micro-computed tomography (?CT) based X-ray histology (XRH) for timely 3D histological imaging during surgery. Key criteria include (1) visualisation of relevant microanatomical structures (2) results in less than 20 minutes during the operation (3) rapid and effective presentation of the data-rich 3D images and (4) compatibility with current intra-operative and post-operative pathology protocols.
For protocol development, pig lung was used as it is similar in size and structure to human lung. Using optimised ?CT scan conditions at our XRH facility in Southampton, consistent 3D imaging of fresh, unfixed peripheral lung samples was demonstrated (n=6), providing relevant microanatomical information in less than 10 minutes (Fig 1). Snap freezing and/or air-inflation of lung samples were also feasible within the time required. Both required additional preparation steps and could lead to over-inflation or affect preparation for routine wax histology, respectively. Short scan times minimised the impact of sample movement on image quality. A system for rapid, automated generation of user-friendly reports was developed. This brings together images and sample details for assessment, patient records and clinical team discussions. To streamline the integration of XRH with existing protocols, we scanned samples in standard containers used to transfer surgical samples to the pathology lab. This allows fast, non-invasive, non-contact scanning in a sealed container, reducing sample handling and avoiding contamination.
The rapid XRH data were judged to be of potential diagnostic quality by pathologists. This approach provides opportunities for future research and diagnostic use.
BibTeX:
@inproceedings{Konstantinopoulou2020a,
  author = {Elena Konstantinopoulou and Orestis L. Katsamenis and Bethany Broadbent and David Chatelet and Philip J Basford and Ian Haig and William Roche and Aiman Alzetani and Philipp Schneider and Peter Lackie},
  title = {Potential assessment of lung samples by X-ray histology (XRH) during surgery},
  booktitle = {10th Annual Tomography for Scientific Advancement (ToScA) symposium (03/09/20)},
  year = {2020},
  url = {https://eprints.soton.ac.uk/448231/}
}
Konstantinopoulou E, Katsamenis OL, Chatelet D, Broadbent B, Basford PJ, Haig I, Roche W, Alzetani A, Schneider P and Lackie P (2020), "Potential for intraoperative assessment of excised lung samples by X-ray histology", In 7th Digital Pathology & AI Congress: Europe (03/12/20 - 04/12/20)., December, 2020.
Abstract: More than 24,000 operations to remove all or part of a patient?s lung take place in Europe each year. The full extent and the type of changes in lung tissue microstructure due to disease may not be evident until surgery is underway, therefore, immediate and informative microanatomical assessment of excised tissue can guide the surgical team or assist with diagnosis.

We explored the feasibility of using micro-Computed Tomography (?CT) based X-ray histology (XRH) for timely 3D histological imaging during surgery. Key criteria considered include: (1) visualisation of relevant microanatomical structures (2) results within the 20-minute intraoperative ?window? (3) rapid and comprehensive presentation of data-rich 3D images and (4) compatibility with current intraoperative and post-operative pathology workflows.

For protocol development, porcine lung was used due to its structural similarities to human lung. Using optimised ?CT scan conditions at our XRH facility in Southampton, consistent 3D imaging of fresh, unfixed, peripheral lung samples was demonstrated (n=6), providing relevant microanatomical information in less than 10 minutes (Fig. 1). Short scan times (under 4 minutes) minimised sample movement artefacts in the images. Snap-freezing and/or air-inflation of lung samples were also feasible within the intraoperative window. However, both required additional sample preparation steps and introduced artefacts (e.g. cracks, movement, cryo-damage of tissue).

Complementing our rapid XRH imaging protocol, a system for fast, automated generation of user-friendly reports was also developed. This brings together sample images and details for assessment, patient records and clinical team discussions. To streamline the integration of XRH with existing protocols we scanned samples in standard containers used to transfer surgical samples to the pathology lab. This allows fast, non-invasive, non-contact scanning in a sealed container, thus reducing sample handling and avoiding contamination.

Pathologists judged the XRH data generated to be of potential diagnostic quality. This approach provides opportunities for both research and diagnostic use.


To find out more and see if 3D X-ray histology can benefit you, please visit www.xrayhistology.org.
BibTeX:
@inproceedings{Konstantinopoulou2020b,
  author = {Elena Konstantinopoulou and Orestis L. Katsamenis and David Chatelet and Bethany Broadbent and Philip J Basford and Ian Haig and William Roche and Aiman Alzetani and Philipp Schneider and Peter Lackie},
  title = {Potential for intraoperative assessment of excised lung samples by X-ray histology},
  booktitle = {7th Digital Pathology & AI Congress: Europe (03/12/20 - 04/12/20)},
  year = {2020},
  url = {https://eprints.soton.ac.uk/448078/}
}
Lawson M, Katsamenis O, Olding M, Larkin O, Smit B, Haig I, Schneider P, Lackie P and Warner J (2020), "3D mapping of blood vessel networks and cells in COPD and non-COPD lung tissue samples using micro-computed tomography and immunofluorescence", In 14.01 - Imaging - European Respiratory Society (ERS) 19th Lung Science Conference (LSC)., mar, 2020. European Respiratory Society.
BibTeX:
@inproceedings{Lawson_2020,
  author = {M Lawson and O Katsamenis and M Olding and O Larkin and B Smit and I Haig and P Schneider and P Lackie and J Warner},
  title = {3D mapping of blood vessel networks and cells in COPD and non-COPD lung tissue samples using micro-computed tomography and immunofluorescence},
  booktitle = {14.01 - Imaging - European Respiratory Society (ERS) 19th Lung Science Conference (LSC)},
  publisher = {European Respiratory Society},
  year = {2020},
  url = {https://openres.ersjournals.com/content/6/suppl_5/21},
  doi = {10.1183/23120541.LSC-2020.21}
}
Ho EML, Rossides C, Pender S, Katsamenis OL, Lackie P and Schneider P (2020), "Semi-automated Intensity-based Image quality assessment with Gaussian Mixture Models", In The 4th Network of European Bioimage Analysts (NEUBIAS) Conference &amp; Symposium 2020 (29/02/20 - 06/03/20)., March, 2020.
Abstract: Protocol development for X-ray micro-computed tomography (microCT) requires optimisation of several factors at once. Quantifying microCT image quality enables objective selection of the most suitable protocol for the user requirements. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) are image quality metrics describing the clarity of a feature in relation to the image noise. SNR and CNR are typically determined by comparing intensities of user-defined regions containing the feature of interest and the background. However, this method is tedious and impractical when comparing between many 3D image datasets. Reiter et al. proposed a region of interest (ROI)-independent method of determining CNR from image intensity distributions of microCT datasets (1). MicroCT intensities are proportional to material- dependent X-ray attenuation, so it is assumed that the overall image intensity for multi-material specimens is the sum of individual Gaussian distributions for each material. Reiter et al. calculate CNR from the means and variances of Gaussians fitted for each material, isolated from the overall image intensity distribution. However, their method is limited to well-separated Gaussians, which is often not applicable in microCT for biological specimens with overlapping image intensity distributions. Here we present a semi-automated tool for determining SNR and CNR from microCT data using Gaussian Mixture Models (GMMs). GMMs estimate the mean, variance and weight of a user-specified number of Gaussian components from the image intensity distribution. These properties are then used to calculate SNR and CNR between any combination of the Gaussian components. This tool was implemented using the Python scikit-learn library (2) and has a custom ImageJ user interface. Validation was performed in silico using a phantom image with pre-defined Gaussian distributions of image intensity for three materials. The phantom image used was a microCT scan of a paraffin-embedded murine colon from a custom-built microCT setup (Nikon Metrology, UK). Materials were segmented by thresholding and image intensities from known distributions of similar specimens were assigned to each pixel, according to the materials represented. The SNR and CNR calculated by GMMs was found to be within 2.5% of the phantom image values. In conclusion, fitting GMMs to the intensity distribution offers a repeatable and objective measurement of image quality for 3D microCT datasets, even from low contrast images with overlapping distributions. Furthermore, SNR and CNR between several material components can be calculated at once without additional user selection of ROIs for each material.
BibTeX:
@inproceedings{soton448072,
  author = {Elaine Ming Li Ho and Charalambos Rossides and Sylvia Pender and Orestis L. Katsamenis and Peter Lackie and Philipp Schneider},
  title = {Semi-automated Intensity-based Image quality assessment with Gaussian Mixture Models},
  booktitle = {The 4th Network of European Bioimage Analysts (NEUBIAS) Conference &amp; Symposium 2020 (29/02/20 - 06/03/20)},
  year = {2020},
  url = {https://eprints.soton.ac.uk/448072/}
}
Ho EML, Rossides C, Pender SLF, Katsamenis OL, Lackie P and Schneider P (2019), "Semi-automated histogram-based image quality assessment with gaussian mixture models", In 7th annual Tomography for Scientific Advancement (ToScA) symposium. Southampton, UK, September, 2019.
BibTeX:
@inproceedings{Ho2019,
  author = {Ho, Elaine M. L. and Rossides, Charalambos and Pender, Sylvia L. F. and Katsamenis, Orestis L. and Lackie, Peter and Schneider, Philipp},
  title = {Semi-automated histogram-based image quality assessment with gaussian mixture models},
  booktitle = {7th annual Tomography for Scientific Advancement (ToScA) symposium},
  year = {2019},
  url = {https://www.toscainternational.org/tosca-UK-2019}
}
Katsamenis OL, Konstantinopoulou E, Basford P, Warner JA, Larkin OJ, Smit B, Haig I, Cox SJ, Sinclair I, Page A, Lackie PM and Schneider P (2019), "3D X-ray histology for biomedical applications at the University of Southampton: Get involved, Get in touch!", In 6th Digital Pathology and AI Congress: Europe. London, UK, December, 2019.
BibTeX:
@inproceedings{Katsamenis2019a,
  author = {Katsamenis, Orestis L. and Konstantinopoulou, Elena and Basford, Philip and Warner, Jane A. and Larkin, Oliver J. and Smit, Bennie and Haig, Ian and Cox, Simon J. and Sinclair, Ian and Page, Anton and Lackie, Peter M. and Schneider, Philipp},
  title = {3D X-ray histology for biomedical applications at the University of Southampton: Get involved, Get in touch!},
  booktitle = {6th Digital Pathology and AI Congress: Europe},
  year = {2019},
  note = {6TH DIGITAL PATHOLOGY & AI CONGRESS: EUROPE LONDON UK, 5-6 December 2019},
  url = {http://www.global-engage.com/event/digital-pathology/}
}
Katsamenis OL, Karavasili C and Fatouros DG (2019), "Assessment of the synergistic antitumour potency of novel drug formulations by means of 3d x-ray histology", In 7th annual Tomography for Scientific Advancement (ToScA) symposium. Southampton, UK, September, 2019.
BibTeX:
@inproceedings{Katsamenis2019b,
  author = {Katsamenis, Orestis L. and Karavasili, Christina and Fatouros, Dimitrios G.},
  title = {Assessment of the synergistic antitumour potency of novel drug formulations by means of 3d x-ray histology},
  booktitle = {7th annual Tomography for Scientific Advancement (ToScA) symposium},
  year = {2019},
  url = {https://www.toscainternational.org/tosca-UK-2019}
}
Lawson M, Katsamenis O, Olding M, Larkin O, Smit B, Haig I, Schneider P, Lackie P and Warner J (2019), "3D mapping of blood vessel networks and cells in COPD and non-COPD lung tissue samples using micro-computed tomography and immunofluorescence", In 7th annual Tomography for Scientific Advancement (ToScA) symposium. Southampton, UK, September, 2019.
BibTeX:
@inproceedings{Lawson2019,
  author = {Lawson, M. and Katsamenis, O. and Olding, M. and Larkin, O. and Smit, B. and Haig, I. and Schneider, P. and Lackie, P. and Warner, J.},
  title = {3D mapping of blood vessel networks and cells in COPD and non-COPD lung tissue samples using micro-computed tomography and immunofluorescence},
  booktitle = {7th annual Tomography for Scientific Advancement (ToScA) symposium},
  year = {2019},
  url = {https://www.toscainternational.org/tosca-UK-2019}
}
O’Brien NS, Leighs JA, Katsamenis OL, Basford PJ, Schneider P, Lackie P, Cox S, Burke M, Michopoulou S, Darekar A and Guy MJ (2019), "Multi-modal research imaging data management at University Hospital Southampton", In 7th annual Tomography for Scientific Advancement (ToScA) symposium. Southampton, UK, September, 2019.
BibTeX:
@inproceedings{O’Brien2019,
  author = {O’Brien, Neil S. and Leighs, James A. and Katsamenis, Orestis L. and Basford, Philip J. and Schneider, Philipp and Lackie, Peter and Cox, Simon and Burke, Martin and Michopoulou, Sofia and Darekar, Angela and Guy, Matthew J.},
  title = {Multi-modal research imaging data management at University Hospital Southampton},
  booktitle = {7th annual Tomography for Scientific Advancement (ToScA) symposium},
  year = {2019},
  url = {https://www.toscainternational.org/tosca-UK-2019}
}
Schneider P (2019), "3D X-ray histology: micro-CT goes medical", In Annual Congress of the European Society of Biomechanics (ESB). Vienna, Austria, July, 2019.
Abstract: Background
Living structures are an intricate three-dimensional (3D) arrangement of cells and tissue matrix across many length scales. Contemporary capabilities to quantify tissue architecture, connectivity and cell relationships are however fundamentally constrained by a lack of 3D analytical platforms with appropriate resolution, penetration, structural differentiation, consistency, volumetric analysis capability and sample throughput. Structural analysis of tissues, whether for research or diagnostic purposes, remains overwhelmingly bounded and constrained by microscopic examination of relatively sparse 2D tissue sections, providing only a snapshot from which 3D spatial relationships can only be inferred. Therefore, whilst 3D medical imaging is commonplace, microscopic tissue structure analysis (i.e., histology) remains overwhelmingly wedded to  200-year-old practices of microscopic 2D examination of tissue sections.
Recent advances
We have demonstrated previously that X-ray imaging by micro-computed tomography (μCT) allows non-invasive 3D imaging of the microstructure of standard tissue biopsies [1]. This yields details comparable to two-dimensional (2D) optical microscope sections but for the whole tissue volume, which can for example overturn misconceptions of disease development based on 2D assessment. One exemplar is the pathogenesis of idiopathic pulmonary fibrosis [2], where 3D structural insight into co-localisation of tissue features and dysmorphia within substantive tissue volumes suggested previously unrecognised fibroblast foci plasticity. Based on this encouraging μCT results for soft tissues, in collaboration with an industrial partner, we developed a custom-design and soft-tissue optimised μCT scanner [3]. Currently, we are establishing the foundations for routine 3D X-ray histology [4], including new X-ray equipment and standardised & automated workflows, where sample throughput will be increased and scan times reduced, providing the foundations for day-to-day 3D X-ray histology.
Future directions
Applicable to vast existing sample archives and a wide range of soft tissue types including musculoskeletal tissues, the technology will open new research areas, such as large-scale 3D histological phenotyping (i.e., histomics). Furthermore, 3D X-ray histology can translate directly into next-generation clinical image-based diagnostics and patient stratification using artificial intelligence and deep learning, and time-critical intraoperative 3D examination of tissue biopsies will become a realistic future target in this research programme. Here, we will present first results of our 3D X-ray histology approach and portray a vision, how high-throughput and non-destructive 3D histological assessment can offer new opportunities in basic biomedical and translational research, following our ambition to provide a day-to-day imaging tool that complements and augments standard 2D histology.
BibTeX:
@inproceedings{Schneider2019,
  author = {Schneider, P.},
  title = {3D X-ray histology: micro-CT goes medical},
  booktitle = {Annual Congress of the European Society of Biomechanics (ESB)},
  year = {2019},
  url = {https://www.conftool.org/esb2019/index.php?page=browseSessions&form_session=112}
}
Schneider P, Katsamenis O, Thomas G, Page A, Cox S, Sinclair I and Lackie P (2019), "Why Every Hospital Should Have a Micro-CT: 3D X-Ray Histology, Let’s Go Beyond Standard 2D Histology", In 22nd International Workshop on Quantitative Musculoskeletal Imaging (QMSKI). Lake Louise, Alberta, Canada, February, 2019.
Abstract: Living structures are an intricate threedimensional (3D) arrangement of cells and tissue matrix across many length scales. Contemporary capabilities to quantify tissue architecture, connectivity and cell relationships are however fundamentally constrained by a lack of 3D analytical platforms with appropriate resolution, penetration, structural differentiation, consistency, volumetric analysis capability and sample throughput. Structural analysis of tissues, whether for research or diagnostic purposes, remains overwhelmingly bounded and constrained by microscopic examination of relatively sparse 2D tissue sections, providing only a snapshot from which 3D spatial relationships can only be inferred. Therefore, whilst 3D medical imaging is commonplace, microscopic tissue structure analysis (i.e., histology) remains overwhelmingly wedded to 200-year-old practices of microscopic 2D examination of tissue sections. We have demonstrated previously that Xray imaging by micro-computed tomography (μCT) allows non-invasive 3D imaging of
the microstructure of standard tissue biopsies 1. This yields details comparable to twodimensional (2D) optical microscope sections but for the whole tissue volume, which can for example overturn misconceptions of disease development based on 2D assessment. One exemplar is the pathogenesis of idiopathic pulmonary fibrosis 2, where 3D structural insight into co-localisation of tissue features and dysmorphia within substantive tissue volumes suggested previously unrecognised fibroblast foci plasticity.
Based on this encouraging μCT results for soft tissues, in collaboration with an industrial partner, we developed a customdesign and soft-tissue optimised μCT scanner (Wellcome Trust Pathfinder Award, 2016- 17). Currently, we are establishing the foundations for routine 3D X-ray histology (Wellcome Trust Biomedical Resource and Technology Development, 2019-2022), including new X-ray equipment and standardised & automated workflows, where sample throughput will be increased and scan times reduced, providing the foundations for day-to-day 3D X-ray histology. Applicable to vast existing sample archives and a wide range of soft tissue types including musculoskeletal tissues, the technology will open new research areas, such as largescale 3D histological phenotyping (i.e., histomics). Furthermore, 3D X-ray histology can translate directly into next-generation clinical image-based diagnostics and patient stratification using artificial intelligence and deep learning, and time-critical intraoperative 3D examination of tissue biopsies will become a realistic future target in this research programme. Here, we will present first results of our 3D Xray histology approach and portray a vision, how high-throughput and non-destructive 3D histological assessment can offer new opportunities in basic biomedical and translational research, following our ambition to provide a day-to-day imaging tool that complements and augments standard 2D histology
BibTeX:
@inproceedings{Schneider2019a,
  author = {Schneider, Philipp and Katsamenis, Orestis and Thomas, Gareth and Page, Anton and Cox, Simon and Sinclair, Ian and Lackie, Peter},
  title = {Why Every Hospital Should Have a Micro-CT: 3D X-Ray Histology, Let’s Go Beyond Standard 2D Histology},
  booktitle = {22nd International Workshop on Quantitative Musculoskeletal Imaging (QMSKI)},
  year = {2019},
  url = {https://www.conftool.org/esb2019/index.php?page=browseSessions&form_session=112}
}
Schneider P (2019), "Engineering, Medicine and Industry team up for technology development in biomedical imaging", In FortisNet 4th Annual Meeting. Southampton, UK, January, 2019.
BibTeX:
@inproceedings{Schneider2019b,
  author = {Schneider, P.},
  title = {Engineering, Medicine and Industry team up for technology development in biomedical imaging},
  booktitle = {FortisNet 4th Annual Meeting},
  year = {2019},
  url = {https://cdn.southampton.ac.uk/assets/imported/transforms/content-block/UsefulDownloads_Download/503413EFFA6A49A49B1C84142EF10EA8/FortisNet%20IV%20branded%20summary%20slides%20for%20web.pdf#_ga=2.241580866.115032613.1559509370-1151691026.1549917520}
}
Schneider P (2019), "Keynote Lecture: Engineering meets medicine in biomedical imaging: laying the foundations for 3D X-ray histology", In Biennial Meeting, Vienna Center for Engineering in Medicine (ViCEM). Vienna, Austria, November, 2019.
BibTeX:
@inproceedings{Schneider2019c,
  author = {Schneider, P.},
  title = {Keynote Lecture: Engineering meets medicine in biomedical imaging: laying the foundations for 3D X-ray histology},
  booktitle = {Biennial Meeting, Vienna Center for Engineering in Medicine (ViCEM)},
  year = {2019},
  note = {2019, “Engineering meets medicine in biomedical imaging: laying the foundationsfor 3D X-ray histology”, Biennial Meeting, Vienna Center for Engineering in Medicine (ViCEM), November 14-15 (2019) https://www.vicem.at/events/ https://www.vicem.at/fileadmin/mediapool-vicem/documents/ViCEM_MeetingNov2019_Agenda.pdf},
  url = {https://www.vicem.at/fileadmin/mediapool-vicem/documents/ViCEM_MeetingNov2019_Agenda.pdf}
}
Schneider P (2019), "Bridging biological and preclinical imaging through 3D X-ray histology", In COMULIS & BioImaging Austria/CMI Conference. Vienna, Austria, November, 2019.
Abstract: Living structures are an intricate three- dimensional (3D) arrangement of cells and tissue matrix across many length scales. However, structural analysis of tissues, whether for research or diagnostic purposes, remains overwhelmingly bounded and constrained by microscopic examination of relatively sparse 2D tissue sections, providing only a snapshot from which 3D spatial relationships can only be inferred. Therefore, whilst 3D medical imaging is commonplace, microscopic tissue structure analysis (i.e., histology) remains overwhelmingly wedded to 200-year-old practices of microscopic 2D examination of tissue sections. We have demonstrated previously that X-ray imaging by micro-computed tomography (µCT) allows noninvasive 3D imaging of the microstructure of standard tissue biosies (Scott et al. 2015, doi:10.1371/journal.pone.0126230). This yields details comparable to two-dimensional (2D) optical microscope sections but for the whole tissue volume, which can for example overturn misconceptions of disease development based on 2D assessment. One exemplar is the pathogenesis of idiopathic pulmonary fibrosis (Jones et al. 2016, doi:10.1172/jci.insight.86375), where 3D structural insight into colocalisation of tissue features suggested previously unrecognised fibroblast foci plasticity. Based on this encouraging µCT results for soft tissues, in collaboration with an industrial partner, we developed a custom-design and soft-tissue optimised µCT scanner that can bridge the gap between biological and preclinical imaging (Katsamenis et al., doi:10.1016/j.ajpath.2019.05.004). Currently, we are establishing the foundations for routine 3D X-ray histology (http://www.xrayhistology.org), including new X-ray equipment and standardised & automated workflows and augmented sample throughput.
Applicable to vast existing sample archives and a wide range of soft tissue types, the technology will open new research areas, such as large-scale 3D histological phenotyping (i.e., histomics). Computing and data handling power is now more than capable of handling the image resolutions and processing required for 3D µCT data analysis and X-ray histology workflows. Furthermore, 3D X-ray histology can translate directly into next-generation clinical image-based diagnostics and patient stratification using
artificial intelligence and deep learning, and time-critical intraoperative 3D examination of tissue biopsies will become a realistic future target in this research programme. Here, we will present first results of our 3D X-ray histology approach and portray a vision, how highthroughput and non-destructive 3D histological assessment can offer new opportunities in basic biology, biomedical and translational research.
BibTeX:
@inproceedings{Schneider2019d,
  author = {Schneider, P.},
  title = {Bridging biological and preclinical imaging through 3D X-ray histology},
  booktitle = {COMULIS & BioImaging Austria/CMI Conference},
  year = {2019},
  note = {2019, “Bridging biological and preclinical imaging through 3D X-ray histology”, COMULIS & BioImaging Austria/CMI Work Group Meetings & Conference, Vienna, Austria, November 20-22 (2019) https://www.comulis.eu/comulis-conference-vienna https://www.comulis.eu/s/Abstractbook.pdf},
  url = {https://static1.squarespace.com/static/5b65562812b13f4790f5df9c/t/5dcc5a2aff2e80648aec22f1/1573673519778/Abstractbook.pdf}
}
Katsamenis OL, Lawson MJ, Olding M, Warner JA, Chatelet DS, Jones MG, Sgalla G, Smit B, Larkin OJ, Haig I, Richeldi L, Lackie PM, Schneider P and Sinclair I (2018), "3D X-ray histology by means of micro- Computed Tomography", In 5thDigital Pathology Congress: Europe. London, UK, December, 2018.
BibTeX:
@inproceedings{Katsamenis2018,
  author = {Katsamenis, O. L. and Lawson, M. J. and Olding, M. and Warner, J. A. and Chatelet, D. S. and Jones, M. G. and Sgalla, G. and Smit, B. and Larkin, O. J. and Haig, I. and Richeldi, L. and Lackie, P. M. and Schneider, P. and Sinclair, I.},
  title = {3D X-ray histology by means of micro- Computed Tomography},
  booktitle = {5thDigital Pathology Congress: Europe},
  year = {2018},
  url = {http://www.giiconference.com/gel560116/}
}
Katsamenis OL, Olding M, Warner JA, Chatelet D, Jones MG, Sgalla G, Smit B, Larkin O, Haig I, Richeldi L, Lackie PM, Schneider P and Sinclair I (2018), "3D X-ray histology by means of micro-computed tomography: A streamline workflow for high-resolution 3D imaging of biopsy specimens", In 6th annual Tomography for Scientific Advancement (ToScA) symposium. Warwick, UK, September, 2018.
BibTeX:
@inproceedings{Katsamenis2018a,
  author = {Katsamenis, O. L. and Olding, M. and Warner, J. A. and Chatelet, D. and Jones, M. G. and Sgalla, G. and Smit, B. and Larkin, O. and Haig, I. and Richeldi, L. and Lackie, P. M. and Schneider, P. and Sinclair, I.},
  title = {3D X-ray histology by means of micro-computed tomography: A streamline workflow for high-resolution 3D imaging of biopsy specimens},
  booktitle = {6th annual Tomography for Scientific Advancement (ToScA) symposium},
  year = {2018},
  url = {https://www.rms.org.uk/discover-engage/event-calendar/tosca-2018.html}
}
Lawson MJ, Katsamenis OL, Olding M, Larkin OJ, Smit B, Haig IG, Schneider P, Lackie PM and Warner JA (2018), "Mapping 3D networks in human lung tissue using micro-computed tomography and immunofluorescence", In 6th annual Tomography for Scientific Advancement (ToScA) symposium. Warwick, UK, September, 2018.
BibTeX:
@inproceedings{Lawson2018,
  author = {Lawson, M. J. and Katsamenis, O. L. and Olding, M. and Larkin, O. J. and Smit, B. and Haig, I. G. and Schneider, P. and Lackie, P. M. and Warner, J. A.},
  title = {Mapping 3D networks in human lung tissue using micro-computed tomography and immunofluorescence},
  booktitle = {6th annual Tomography for Scientific Advancement (ToScA) symposium},
  year = {2018},
  url = {https://www.rms.org.uk/discover-engage/event-calendar/tosca-2018.html}
}
Lawson MJ, Katsamenis OL, Olding M, Larkin OJ, Smit B, G.Haig I, Schneider P, Lackie PM and Warner JA (2017), "Correlative microfocus computed tomography and fluorescence microscopy of fixed human lung tissue", In 5th annual Tomography for Scientific Advancement (ToScA) symposium. Portsmouth, UK, September, 2017.
BibTeX:
@inproceedings{Lawson2017,
  author = {Lawson, M. J. and Katsamenis, O. L. and Olding, M. and Larkin, O. J. and Smit, B. and G.Haig, I. and Schneider, P. and Lackie, P. M. and Warner, J. A.},
  title = {Correlative microfocus computed tomography and fluorescence microscopy of fixed human lung tissue},
  booktitle = {5th annual Tomography for Scientific Advancement (ToScA) symposium},
  year = {2017},
  url = {https://www.rms.org.uk/discover-engage/event-calendar/tosca-2017.html}
}
Rossides. C, Katsamenis OL, Larkin. OJ, Smit. B, Haig. IG, Sinclair. I, Pender. SLF and Schneider P (2017), "Micro-computed tomography optimised for soft tissues: first steps towards early diagnosis of colorectal cancer", In 5th annual Tomography for Scientific Advancement (ToScA) symposium. Portsmouth, UK, September, 2017.
BibTeX:
@inproceedings{Rossides.2017,
  author = {Rossides., C. and Katsamenis, O. L. and Larkin., O. J. and Smit., B. and Haig., I. G. and Sinclair., I. and Pender., S. L. F. and Schneider, P.},
  title = {Micro-computed tomography optimised for soft tissues: first steps towards early diagnosis of colorectal cancer},
  booktitle = {5th annual Tomography for Scientific Advancement (ToScA) symposium},
  year = {2017},
  url = {https://www.rms.org.uk/discover-engage/event-calendar/tosca-2017.html}
}
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